About: Emission prediction of a thermal power plant     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • The task of prediction of emissions is very challenging and also important. We argued that simple learning techniques that learn only one predictive model are not powerful enough in more complex situations. Better predictive results can be achieved by splitting data into smaller parts and for each part to learn a sub-model. We proposed and tested a novel method that combines meta-learning and ensemble learning. We showed that there is significant increase in prediction accuracy.
  • The task of prediction of emissions is very challenging and also important. We argued that simple learning techniques that learn only one predictive model are not powerful enough in more complex situations. Better predictive results can be achieved by splitting data into smaller parts and for each part to learn a sub-model. We proposed and tested a novel method that combines meta-learning and ensemble learning. We showed that there is significant increase in prediction accuracy. (en)
Title
  • Emission prediction of a thermal power plant
  • Emission prediction of a thermal power plant (en)
skos:prefLabel
  • Emission prediction of a thermal power plant
  • Emission prediction of a thermal power plant (en)
skos:notation
  • RIV/00216224:14330/14:00077069!RIV15-MSM-14330___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 14418
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/14:00077069
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • meta-learning; model prediction; boiler; NOx (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [F385646E3321]
http://linked.open...v/mistoKonaniAkce
  • Jasná pod Chopkom, Nízké Tatry, Slovakia
http://linked.open...i/riv/mistoVydani
  • Praha
http://linked.open...i/riv/nazevZdroje
  • Znalosti 2014
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Křehlík, Karel
  • Popelínský, Lubomír
  • Jurčo, Juraj
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Vysoká škola ekonomická v Praze
https://schema.org/isbn
  • 9788024520544
http://localhost/t...ganizacniJednotka
  • 14330
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software